Introducing Monte Carlo Methods with R
Computational techniques based on simulation have now become an essential part of the statistician's toolbox. It is thus crucial to provide statisticians with a practical understanding of those methods, and there is no better way to develop intuition and
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· Kurt Hornik · Giovanni Parmigiani
For other titles published in this series, go to http://www.springer.com/series/6991
Christian P. Robert · George Casella
Introducing Monte Carlo Methods with R
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Christian P. Robert Universit´e Paris Dauphine UMR CNRS 7534 CEREMADE place du Mar´echal de Lattre de Tassigny 75775 Paris cedex 16 France [email protected]
George Casella Department of Statistics University of Florida 103 Griffin-Floyd Hall Gainesville FL 32611-8545 USA [email protected]
Series Editors Robert Gentleman Department of Bioinformatics and Computational Biology Genentech South San Francisco CA 94080 USA
Kurt Hornik Department of Statistik and Mathematik Wirtshchaftsuniversit¨at Wien Augasse 2-6 A-1090 Wien Austria
Giovanni Parmigiani Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute 44 Binney Street Boston, MA 02115 USA
ISBN 978-1-4419-1575-7 DOI 10.1007/978-1-4419-1576-4
e-ISBN 978-1-4419-1576-4
Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2009941076 c Springer Science+Business Media, LLC 2010 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
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To our parents, who taught us much in many ways.
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“What if you haven’t the data?” “Then we shall proceed directly to the brandy and cigars.” Lyndsay Faye The Case of Colonel Warbuton’s Madness
Preface
“After that, it was down to attitude.” Ian Rankin Black & Blue The purpose of this book is to provide a self-contained entry into Monte Carlo computational techniques. First and foremost, it must not be confused with a programming addendum to our earlier book Monte Carlo Statistical Methods whose second edition came out in 2004. The current book has a different purpose, namely to make a general audience familiar with the programming aspects of Monte Carlo methodology through practical implementation. Not only have we introduced R at the core of this book, but the emphasis and contents have changed drastically from Monte Carlo Statistical Methods, even though the overall vision remains the same. Theoretical foundations are intentionally avoided in the current book. Indeed, the emphasis on practice is a major feature of this book in that its primary audience consists of graduate students in statistics
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